What Do We Really Know About VBID? Quality of the Evidence and Ethical Considerations for Health Plan Sponsors

Advocates of value-based insurance design (VBID) have argued based on break-even economic modeling that VBID can be effective but acknowledge that direct medical savings from increased use of services with strong evidence of clinical benefit are unlikely to finance the entire [VBID] investment in the short term. Thus, these VBID proponents support investments in processes to define low-value care and a benefit design that couples cost-sharing reductions for high-value services with cost-sharing increases for services not identified as high value. This suggestion has led to an important emerging issue for employers considering VBID adoption, provider and patient acceptance of higher levels of cost-sharing for services deemed low-value. Since publication of our earlier observations about deficiencies in research on VBID, new copayment reduction studies using nonrandomized comparison groups have been published, and an additional study measured the association between medication adherence and all-cause health care costs. Although all the VBID studies provided evidence that implementation of VBID might have a small favorable effect on medication adherence, none provided the information that payers need to make an informed decision about VBID because of serious problems in reporting, program design, and effect calculation. None of the new VBID studies reported its effect on generic drug utilization, and none reported the cost of the intervention to the payer. There are still no randomized controlled trials of VBID. Thus, nearly a decade after pharmacy benefit copayment reduction was initially proposed as a means to improve the outcomes of patients with chronic health conditions, health plan sponsors have little of the information that they need to assess the costs and benefits of VBID.A follow-up article on the subject of this editorial is available here: VBID, the PPACA, and FREEE Medications: Did Politics Trump the Evidence About Cost Sharing?

I n March 2009, the Agency for Healthcare Research and Quality (AHRQ) convened a meeting of "policymakers, researchers, and producers of health care data" to "begin developing a strategy to optimize the availability of information and data for enactment and implementation of health care reform." 1 The needs described by participants were as expected: timely information about "the likely concrete effects of unique, specific policy proposals," provided with an eye to "the specific levers available to policymakers," developed with a "clear and transparent" methodology, and assessing "the impact on the public sector and consumer." It is telling that the need for "solid data" was emphasized by "veterans of past health care reform efforts," who also observed that current data needs "are much broader." 1 Data Promulgated Versus Data Used : Is There a Credibility Gap? The AHRQ's envisioned role for accurate and transparent data in developing and monitoring a redesigned health care system represents an optimal scenario-if health care research "builds it," policymakers "will come." Yet, the ways in which health plan sponsors actually obtain and use information in making benefit design decisions may not match this expectation. A Diamond Management/Willis North America survey of large and small employers in a variety of industry sectors, conducted after passage of the Patient Protection and Affordable Care Act (PPACA) using an unreported sampling methodology, found that a slight majority (736 of 1,400, 52.6%) of respondents cited "in-house personnel" as their primary source of information about "the health care reform statute or regulations." 2 Insurance brokers and carriers were cited as a primary information source by 25.1% and 6.6%, respectively. Only 5.2% said that their primary information source was "free resources and tools as published by government agencies." 2 Recent news reports also suggest that employers currently rely primarily on consultants to guide their planning for implementation of PPACA, including choices of cost-sharing levels and benefit designs. 3 Similarly, only 6% of human resource and benefits managers responding to a 2010 Kaiser Family Foundation/ Health Research & Educational Trust health benefits survey (N = 2,046, response rate 47%) reported that they "review performance indicators for their health plan's service or clinical quality," and of that small group, only 18% reported using Healthcare Effectiveness Data and Information Set (HEDIS) measures promulgated by the National Committee for Quality Assurance. 4 Various factors may explain employers' apparent reluctance or inability to use externally promulgated information about health care policy and quality. One is organizational size; large and small employers generally exhibit markedly different responses to external change. 2,4 However, as we have observed previously, another possible reason for what appears to be inexplicable indifference to the guidance of external "experts" is appropriate wariness about recommendations that have not yet been tested in rigorous research. 5 That is, the most skeptical decision makers may be the best informed about the limitations of available evidence. A growing body of work suggests that even widely used standards, such as ambulatory care metrics that are endorsed by key quality measurement organizations 6 and infectious disease treatment guidelines promulgated by the Infectious Diseases Society of America, 7 are commonly supported primarily by expert opinion or a methodologically suboptimal evidence base. Moreover, guidelines supported solely by observational evidence and/or expert opinion are commonly refuted and replaced when subjected to the more rigorous test of a randomized controlled trial. 8

Slow Uptake of VBID: Information Gap or Sensible Decision Making by Plan Sponsors?
The Rx Outcomes Adviser, a recently launched blog intended to provide health plan sponsors with actionable and evidencebased information about pharmacy benefits, highlighted in an early posting the costs and benefits of value-based insurance design (VBID), the lowering or waiving of copayments for "high-value" medications in an effort to increase their use. 9 Because the blog's purpose is to help decision makers navigate the challenge of reviewing and applying health outcomes research to make well-informed policy decisions, 10 a focus on the cost-effectiveness of VBID is particularly appropriate.

E D I T O R I A L
www.amcp.org Vol. 17 and implementing or enhancing clinical disease management programs (DMPs). [23][24][25][26][27][28] The annual drug trend reports (DTRs) of PBMs, which reflect their marketplace strategies and benefit design recommendations, suggest a recognition that nonadherence is a multifaceted phenomenon encompassing negative perceptions about medications and side effects, patient characteristics (e.g., low literacy, forgetfulness), and therapeutic complexity requiring pharmacist intervention. [24][25][26][27][28] However, the topic of VBID has not been avoided altogether by PBMs. A few PBMs have reported observational investigations of the association between out-of-pocket cost and medication use 27,29,30 or between medication adherence and all-cause health care costs. 31 In a balanced approach to VBID, a health plan-owned PBM advises against zero-dollar copayments because "even as little as $5 per prescription gives the benefit more perceived value to members;" suggests that plan sponsors "carefully consider whether value-based pharmacy benefits are a good fit" for members with adherence of less than 80% for medications to treat diabetes, high blood pressure, or dyslipidemia; and recommends that to improve cost-effectiveness, sponsors consider copayment reductions for generic drugs only. 28 These observations, and the advice of most PBMs to use a variety of tools and messaging strategies to improve adherence, are consistent with behavioral economics research suggesting that consumer purchasing behavior is neither entirely rational nor based solely on price. 32 Peer-reviewed evidence about the reasons for payers' reluctance to adopt copayment reduction strategies is currently unavailable. However, popular press and industry reports suggest that major factors in the slow uptake for VBID include (a) the "potential for short-term increase in utilization and cost" with "uncertain" health benefits, 21,33 (b) the possibility of "unintended incentives" that could reduce generic drug utilization if brand drug copayments are reduced too much, 33 and (c) synergies between business interests and the use of alternative adherence promotion strategies. 23

Payer Perspectives on High Cost and Uncertain Evidence for VBID
A PBM medical officer interviewed for an October 2009 report on novel business models in the PBM industry cited a focus on improving medication adherence as an important market niche. Although noting that medication nonadherence represents a "tremendous opportunity ... to lower medical costs, like [emergency room] visits for asthmatics," the PBM executive argued against using copayment waivers to promote adherence, largely because of the high cost of VBID relative to other strategies that the PBM advocates as more effective: "Benefit designs that eliminate copays increase compliance by 1 to 5 percent, but a company takes on a huge additional expense by absorbing the copay. We found that moving patients to [mail order pharmacy] is the single most important thing you can Section 2713(a) of the PPACA calls for the creation of guidelines to "permit a group health plan and a health insurance issuer offering group or individual health insurance coverage to utilize [VBID]," 11 suggesting that whether to adopt a VBID for the drug benefit may become an increasingly important question for payers.
Yet, despite being launched more than 9 years ago as "a concept that stands on science and equity" 12 and sustained by financial support from the pharmaceutical industry 13,14 and enthusiastic popular press coverage, 15-17 VBID (initially termed "benefit-based copay") has not caught on among the majority of health plan sponsors. Recent VBID use rates are estimated at approximately 20%, and plan deductibles over the past few years have generally trended higher, not lower. [18][19][20][21][22] For example, when 507 employers with at least 1,000 employees were asked in the 2010 National Business Group on Health/Towers Watson (NBGH/TW) survey to indicate benefit design strategies that they had used during 2010, reductions in "pharmacy copays or coinsurance for those with chronic conditions" were cited by 19% of employers. Of 37 strategies mentioned in the 2010 survey, only 2 were used less often than copayment reductions: increasing the use of selective provider networks and providing incentives to use personal health records. In contrast, 23% of employers reported having "significantly" increased "pharmacy copays, deductibles or coinsurance" in 2010; 54% reported offering a consumer-directed (high-deductible) health plan (CDHP); and the percentage of CDHPs covering "preventive prescription drugs" at 100% (i.e., no patient cost-sharing) was just 20%. 18 When asked about their plans for 2011, 28% of employers reported planning to significantly increase pharmacy cost-sharing requirements, and total estimated CDHP availability was expected to grow to 61%. 18 Although reluctance to expend funds on health care in a declining economy was no doubt partly responsible for these trends, it is notable that employers were willing to make investments in other areas. For example, the percentages offering programs for lifestyle behavioral change, health coaching, and smoking cessation were 50%, 56%, and 76%, respectively. 18 Another indication of lukewarm interest in VBID is the less-than-enthusiastic treatment it receives from most large pharmacy benefits management (PBM) companies. This phenomenon is curious and worthy of attention because PBMs can be exceptionally customer-focused and would presumably embrace customer demands that are popular in the marketplace, since they typically do not bear financial risk (e.g., capitation) for the cost of pharmacy benefits. Yet, instead of pharmacy copayment reduction intended to improve medication adherence, PBMs focus more attention on alternative strategies that include dispensing medication in 90-day supplies, increasing direct contact between pharmacists and patients, providing targeted refill reminders to nonadherent patients, do to improve adherence." 23 The DTR of a health plan-owned PBM similarly acknowledges that "quantifying the [return-oninvestment] for [VBID] is challenging" because "medical costs avoided, improved quality of life, reduced absenteeism and other positive outcomes are often cited but can be lost when incentives are applied too broadly." 28 Popular press interviews with benefit design consultants reported in May 2009 also suggested that cost relative to uncertain benefit is an important consideration for employers in making decisions about VBID, with one consultant noting that because of the economic downturn "it's a little bit harder to get approval for reducing copays, especially when results are a little bit squishy" and another suggesting that growth in the copayment waiver trend is limited because "there's not a ton of data" about the effects of VBID on overall medical cost. 21 Nonetheless, a November 2010 press report on adopters of VBID suggested that the estimated 18% of employers with a chronic medication copayment waiver or reduction in place as of 2009 "are convinced this [approach] works, despite an absence of rigorous research to back them up." 20 Still, lack of reliable evidence about VBID may not be the only reason for tepid response to it by most PBMs. First, PBMs that own mail order pharmacies have an interest in using copayment incentives to encourage use of mail order by refill customers and might be expected for business reasons to recommend 90-day supplies, although some PBMs recommend 90-day dispensing for community pharmacies as well as mail order. 28 Second, PBMs may be reluctant to recommend copayment reductions for brand medications for reasons that include client preference and higher profit margins on generic than brand drugs because of "spread" pricing. 23 Notably, however, research evidence suggests that both of these PBM business interests are congruent with the needs of health care consumers. That is, consistent with PBM recommendations, mail order use is cost-effective for plan sponsors 34 and positively associated with adherence to chronic medication therapy, 35,36 although randomized trials of the effects of mail order pharmacy use on patient outcomes are clearly needed. 37 Also supporting PBM recommendations are the findings of AHRQ-funded comparative effectiveness analyses suggesting that generic medications for high-prevalence chronic conditions, such as hypertension and diabetes, 38,39 on average provide equivalent therapeutic effect at equivalent or better safety-a remarkable bargain for patients considering that 90-day supplies of generic drugs to treat high-prevalence chronic conditions are commonly available for $10-$12 in large community pharmacies. 40 Proposal to Offset VBID Costs: Higher Cost Sharing for "Low-Value" Services VBID proponents rightly point out that the net total cost of a VBID program consisting only of copayment reductions "critically depends on whether the incremental spending on the targeted services, such as hypertension medication, can be offset through a decrease in adverse events, such as hospitalizations." 41 In other words, does a health plan sponsor that pays for both medical and pharmacy benefits and incurs higher pharmacy benefit costs because of reducing or waiving copayments for medications to treat high-prevalence chronic conditions (e.g., diabetes, hypertension, dyslipidemia) reap the benefit of healthier enrollees who incur fewer catastrophic medical events (e.g., myocardial infarctions [MIs], strokes) as a result of increased medication use? More importantly, do health plan members-who ultimately pay a portion of the cost of health policy decisions in their share of health plan premiums-experience increased, decreased, or unchanged health benefits when the health plan sponsor implements VBID copayment reduction?
A transparent "plausibility calculator" analysis, designed and reported by Melnick and Motheral in the March 2010 issue of JMCP, suggests that "health plan sponsors are highly unlikely to experience net savings by implementing VBID programs, even under generous assumptions, for 2 reasons." 42 First, price elasticity for medications is generally low in commercially insured groups, meaning that most copayment reductions go to patients who would have been equally compliant without the copayment savings. Second, in a population of commercially insured enrollees "with varying risk levels," the baseline risk of avoidable expensive medical events (e.g., emergency room [ER] visits and hospitalizations) is low, meaning that it is mathematically nearly impossible for increased medication compliance to prevent a sufficient number of expensive events to offset the costs of copayment reductions. 42 Advocates of VBID have argued based on "break-even" economic modeling that VBID "can be effective" 43 but acknowledge that "direct medical savings from increased use of services with strong evidence of clinical benefit are unlikely to finance the entire [VBID] investment in the short term." 41 Thus, these VBID proponents support "investments in processes to define low-value care" and a benefit design that "couples cost-sharing reductions for high-value services with cost-sharing increases for services not identified as high value." 41 This suggestion has led to an important emerging issue for employers considering VBID adoption-provider and patient acceptance of higher levels of cost-sharing for services deemed "low-value." 19,41,44 The Payer's Dilemma: Value to Whom? Methods for defining a "low-value" service are in their nascence and are far from straightforward.  have suggested that services should be defined as "low-value" if they "result in harm-for example, services with D designation that are discouraged by the [U.S.] Preventive Services Task Force" (USPSTF)-or, more broadly, if their cost is "deemed too expensive for the health benefits produced." 41

What Do We Really Know About VBID? Quality of the Evidence and Ethical Considerations for Health Plan Sponsors
Health economist James Robinson has argued that "low-value" services should be subsets of "high-cost health services," such as "biopharmaceuticals, implantable medical devices, advanced imaging modalities, and specialized surgical procedures." 44 Various methods would be used to determine which highcost services would fall into the "low-value" subset, depending on the clinical circumstances. For biopharmaceuticals, for example, Robinson proposes that value might be defined based on the patient's "clinical indication, disease severity, and comorbidities," perhaps in conjunction with practice setting characteristics including "physician specialty, the presence of care coordination, and patient education services." He suggests that U.S. Food and Drug Administration (FDA) approval might also be used as an indication of value (i.e., drugs used off-label would be subject to higher patient cost sharing), perhaps in conjunction with a drug compendium or "an authoritative, evidence-based care pathway." 44 For implantable devices (e.g., stents, pacemakers), he proposes that payers "cover the basicfunction device, leaving the patient to buy up to a higherfunction alternative-unless the higher-function device were known to offer a clinically better outcome to this particular type of patient" as determined by "the health plan's medical management professionals in consultation with the patient's physician." 44 And, for common surgeries, such as knee replacements, "the insurer could specify a contribution that it would make, with the contribution based on the payment rate for the most efficient provider team in the local market. The patient would be assigned responsibility for paying the extra costs incurred if a higher-price provider team is chosen." 44 Putting aside the complexity of designing, maintaining, and administering a system like that envisioned by Robinson, 2 important and potentially controversial issues are apparent.
Whose "Evidence-Based Conclusion" Prevails in Determining "Value?" First, key organizations, viewing the same evidence, often reach different conclusions about the value of medical services. For example, the suggestion by Fendrick et al. 41 to assign a "low-value" designation to USPSTF "D" services is reasonable, but the USPSTF currently has a D designation for teaching women to perform monthly breast self-examinations (BSE) 45 and, at this writing, appears poised to give prostate cancer screenings for men in all age groups a D designation in an upcoming meeting. 46 In contrast, screening guidelines promulgated by the American Cancer Society (ACS) describe BSE training and prostate cancer screening as options that should be made available to patients and providers, depending on the patient's level of risk and personal preferences. [47][48][49] Similarly, the USPSTF currently has a C designation for mammography before the age of 50 years, meaning that the USPSTF "recommends against routinely providing the service" because "there is at least moderate certainty that the net benefit [of the service] is small" after accounting for both benefits and harms associated with the screening process; these harms include primarily "psychological harms, unnecessary imaging tests and biopsies in women without cancer, and inconvenience due to false-positive screening results" and "overdiagnosis," defined as the detection and treatment "of cancer that would never have become clinically apparent." 50 Nonetheless, the USPSTF recognizes the possibility of "considerations that support providing the service in an individual patient," including "the patient's values regarding specific benefits and harms." 50 In contrast, the ACS recommends annual mammograms beginning at 40 years of age "and continuing for as long as a woman is in good health." 51 The American College of Radiology (ACR) goes a step further in describing the value of screening mammography for women aged 40 to 49 years, calling the USPSTF recommendations "ill advised and dangerous" and "unconscionable," describing annual mammography screening for women aged 40 years or older as "one of the major health care advances of the past 40 years," and arguing that the USPSTF "selectively reviewed the literature, ignoring hundreds of well-regarded studies on the subject." 52 This controversy leaves a payer that is trying to define cost-sharing levels based on "value" with an obvious and seemingly irreconcilable conundrum: which evidence-based conclusion should the payer adopt in determining the value of mammography for women aged 40 to 49 years-that of the USPSTF, the ACS, or the ACR?

Ethical Considerations in Deeming Services "Low-Value"
When Evidence is Uncertain. Second and more important, a policy of redirecting scarce resources from one patient group (users of high-cost medical services, often for catastrophic illness) to another patient group (users of chronic medication therapy for high-prevalence conditions, often for primary prevention) has profound ethical implications that require thoughtful consideration of the evidence about the proposed policy change. In other words, consistent with the principles of comparative effectiveness research, appropriate and ethical resource allocation requires reliable and valid evidence about the costs and benefits of available alternatives. Yet, as Choudhry et al. (2010) observed in a recent review, "there is a paucity of data to indicate for which services cost sharing should be increased," as well as a "lack of evidence" about whether drug copayment reductions "will yield better health outcomes and lead to reductions in other health care costs." 11 This lack of evidence makes the resource allocation shifts suggested by VBID proponents ethically questionable at the present time.
These ethical implications become even more cogent when one considers the possibility that reduced brand drug copayments could potentially incentivize patients to use brand medications for therapeutic purposes that could be served with generics, a phenomenon of "unintended incentives." 33 Such incentives reduce the affordability of the benefit, both overall What Do We Really Know About VBID?

Quality of the Evidence and Ethical Considerations for Health Plan Sponsors
and-a point that often goes unnoticed-for the individual patient who pays an unnecessarily high, albeit reduced, copayment for the brand drug.
The clinical implications of potentially encouraging greater first-line brand drug use should also be thoughtfully considered because the risks and benefits of newer medications are sometimes not as fully understood prior to FDA approval as they are in the postmarketing phase. The history of rosiglitazone-a top-selling diabetes drug that was initially approved in 1999 but "significantly" restricted by the FDA in September 2010 because new studies suggested that it elevated cardiovascular event risk-provides a case in point. 53,54 Early Responses to Defining "Low-Value" Services. Given these uncertainties, it is perhaps not surprising that early efforts to implement VBID programs encompassing both copayment reductions for "high-value" services and copayment increases for "low-value" services have been met with skepticism and controversy. In March 2010, Kaiser Health News reported that 5 insurers in Oregon had begun offering a benefit design that provided free or low-cost physician visits and prescription drugs for certain chronic conditions (asthma, congestive heart failure, diabetes, depression, heart disease, chronic bronchitis, and emphysema) but required much higher patient cost sharing for "treatments deemed overused." 55 Patients using targeted "overused" treatments-such as knee or hip replacement, coronary artery bypass surgery, stent placement, hysterectomy, certain imaging examinations, and ER visits-would pay double the usual plan deductible, double the office visit copayment, and up to one-half of hospitalization and ER cost, up to an annual out-of-pocket maximum of $1,500 for individuals and $3,000 for families. Only 1 employer, a steel manufacturer, adopted the plan offering, and its head of benefits estimated that only 7% of workers would select it. 55 Detractors of this and similar VBIDs argue that the designs fall into a "danger zone of limiting access to medical care" and that they represent "too much of a blunt instrument." 55 For example, not every patient with heart disease can be treated medically instead of surgically, and "while researchers say that, overall, too many hysterectomies are performed, women with uterine cancer have little choice." 55 When the state of Oregon implemented a similar VBID for its public employees in 2010, its planning group "ruled out including cardiac treatments and hysterectomy in the higher-cost [category of] coverage because doing so was considered too contentious." 56

Inaccurate Descriptions Hamper Efforts to Evaluate VBID
The important task of finding answers to the question of VBID's effectiveness in improving patient health has been complicated by deficiencies in the base of evidence about pharmacy benefit copayment change. We noted in a 2008 editorial that evidence suggesting an effect of VBID on medication adherence was scant and methodologically nontransparent. 57 We have also noted that the "case" for the negative effect of typical copayment increases on adherence has been made primarily with research employing observational designs in which association was sometimes erroneously equated with causation; quasiexperimental (pre vs. post with comparison group) studies of typical copayment increases in commercially insured groups have generally found positive outcomes for patients and plan sponsors. 8,[58][59][60][61] Unfortunately, much of the literature on cost sharing has tended to overstate or misstate previous research findings, suggesting that cost sharing had a greater influence on medication adherence than was actually documented in the original work. For example, in discussions of cross-sectional analyses comparing higher versus lower cost sharing levels, one sometimes sees references to "price responsiveness" to "[copayment] changes" when no copayment change was measured 58 or to "adherence" outcomes from studies that included no measures of adherence; 57 and seemingly small but often substantively important discrepancies are common. In a recent example, a 2008 study by Sedjo and Cox 62 of changes in statin utilization following simvastatin (Zocor) patent expiration was among the studies cited in the introduction to a research article to support a statement that medication adherence increases by 2%-5% in the first year after VBID implementation. 63 Sedjo and Cox did find that following simvastatin patent expiration and the resulting change from a brand to generic copayment (not a VBID program implementation), the medication possession ratio (MPR) for simvastatin users increased by a mean adjusted 0.52%, compared with an MPR decline of 2.02% for users of brand statins other than simvastatin, who experienced no copayment decrease. However, they also found that among patients who experienced the greatest copayment decreases measured in the study, more than $15, price elasticity was -0.02-that is, no meaningful price responsiveness; and, they found that the percentages of patients whose MPR increased from less than 80% before patent expiration to at least 80% after patent expiration were 10.5% in the simvastatin group and 10.0% in the group using other brand statins-that is, no meaningful difference. 62 A more serious discrepancy appeared in the introduction to a recently published research article, in which a study by Huskamp et al. (2003) was cited to support the statement that "prescription drug benefits that shift greater costs to consumers or increase barriers to access can result in lower rates of drug treatment, poorer adherence, and increased rates of treatment discontinuation." 29 This description is inconsistent with the actual finding of Huskamp et al. that a change from a single-tier $7 copayment to a 3-tier $8/$15/$30 benefit, but not a change from a 2-tier $6/$12 to a 3-tier $6/$12/$24 benefit, was associated with a reduced probability of using medication in 3 therapy classes (proton pump inhibitors, What Do We Really Know About VBID? Quality of the Evidence and Ethical Considerations for Health Plan Sponsors care costs (Appendix). Although all the VBID studies provided evidence that implementation of VBID might have a small favorable effect on medication adherence, none provided the information that payers need to make an informed decision about VBID because of serious problems in reporting, program design, and effect calculation.
No Information About Generic Utilization. None of the new studies of VBID reported its effect on generic utilization, 29,63,68-71 an especially important omission for programs in which copayment reductions either included brand drugs 29,68,70 or were limited to brand drugs. 69,71 Failure to report the effects of brand drug copayment decreases on generic drug utilization is especially problematic because previous observational investigations have found an association between prescription drug cost-sharing increases and increased use of lower-cost medications (i.e., generic and preferred brand drugs) in the same therapeutic class. 58,61 No Information About Payer Cost. None of the new VBID studies reported the cost of the intervention to the payer. 29,63,[68][69][70][71] A report by Gibson et al. (2011a) of a program in which coinsurance rates for brand antidiabetic drugs were reduced-from 20% for tier 2 and 35% for tier 3 to the 10% level previously in place only for generic medications-is especially notable because it purported to show a favorable return-on-investment (ROI) attributable to medical cost offsets but actually measured total costs, not payer costs. 71 In other words, the calculation ignored the cost to the employer for the copayment waivers (i.e., the cost shift from patient to payer); thus, its results do not represent ROI from the payer perspective. The report also indicated significant effects for VBID only for a subgroup of patients enrolled in a DMP but did not report the cost of the DMP. This omission of DMP costs is especially important because the program was intensive, including nurse telephone outreach, coaching, and monitoring, in addition to numerous written educational components. 71 Thus, despite the indication in the article's title that VBID coupled with a DMP "produced savings," the study did not address that research question.
In another report by Gibson et al. (2011b) of a copayment reduction intervention for medications to treat diabetes, asthma, and hypertension, the authors "raise the prospect that this program may have saved the company money by reducing other medical costs" because "clinical effects such as changes in glucose levels, blood pressure, and lung functioning might have occurred," but no assessment of these measures was made, and the report's quantitative analysis indicated no significant association between VBID and any of 3 measures of spending (pharmaceutical, medical, or total) during the 3-year post-implementation period. 70 The study report also transparently disclosed 2 important confounding factors-a DMP was phased in for the VBID employer during the postimplementation period, and the VBID employer was a pharmaceutical manufacturer that provided its brand drugs free of angiotensin-converting enzyme [ACE] inhibitors, and statins). 61 More importantly, Huskamp et al. found that treatment discontinuation rates were significantly higher for patients who experienced a $23 copayment increase (from $7 to $30) but not for patients who experienced a $12 copayment increase (from $12 to $24). And, perhaps because of type 1 error or an unmeasured confounder, among patients taking ACE inhibitors, treatment discontinuation rates were lower (not higher) for the patients who experienced a copayment increase from $12 to $24 than for patients whose copayments remained unchanged at $12-that is, persistence with ACE inhibitor therapy was better for patients with a higher copayment. 61 The Huskamp et al. study has been inaccurately described elsewhere including a 2008 commentary, which indicated that "when an employer increased cost-sharing requirements by about $10 to $20 per prescription … 21% of patients stopped taking their medication for high cholesterol (compared with 11% in a control group);" 64 the actual research finding by Huskamp et al. for a group experiencing a copayment increase of approximately $10 was that 3 of 33 (9.1%) statin users whose copayment increased by $12 versus 1 of 25 (4.0%) statin users without a copayment increase discontinued statin use, a nonsignificant difference (P = 0.45). 61 The same commentary, an assessment of policy implications from the Rand Health Insurance Experiment (RHIE) and selected observational studies, indicated that by discouraging use of appropriate health care services, cost sharing "could lead to additional hospitalization, emergency department visits, and even death." 64 The RHIE did find that higher levels of cost sharing led to reduction in use of health care services, including both those deemed essential and nonessential by RHIE investigators; yet, the RHIE found that these service use reductions had no effects on health except for a few minor outcomes (e.g., vision, dental, and increase of an average 3 millimeters mercury [mm Hg] in diastolic blood pressure) that were limited to low-income RHIE enrollees only. 65,66 In contrast to the commentary's portrayal, RHIE authors even argued in 1987 and 1992 that their finding of "enormous potential savings" from cost sharing, with "little apparent health impact on the kind of people who typically are covered under employer health insurance," may have prompted plan sponsors to increase coinsurance and deductibles in the years immediately following the RHIE's publication, resulting in large health care cost savings nationwide. 65,67 New Observational Evidence About VBID Copayment Reduction Since publication of our earlier observations about deficiencies in research on VBID, 8,57 new copayment reduction studies using nonrandomized comparison groups have been published, 29,62,63,[68][69][70][71] and an additional study 31 measured the association between medication adherence and all-cause health What Do We Really Know About VBID? Quality of the Evidence and Ethical Considerations for Health Plan Sponsors not contain the patient subgroup counts necessary to calculate unbiased discontinuation rates for the study groups.
Less serious but still important is a problem with attributed causal linkage that appears in a transparent and clearly reported analysis by Roebuck et al. (2011) of the association between medication adherence and all-cause health care costs. 31 In that analysis, the authors made no assessment of whether the observed all-cause utilization could reasonably be clinically attributed to medication nonadherence (e.g., cardiovascular events vs. automobile accidents); the authors chose instead to rely solely on fixed-effects statistical modeling techniques to establish causal linkage, a suboptimal method for observational analysis. 72 Additionally, the authors assumed that a patient with a chronic disease diagnosis (heart failure, diabetes, hypertension, or dyslipidemia) but without pharmacy claims had medication adherence of zero, regardless of whether any medication was prescribed. This decision excludes the possibility of nonpharmacologic interventions based on lifestyle modification and is, although appropriate for heart failure, inconsistent or only partly consistent with treatment guidelines for the other 3 disease states. [73][74][75] Another problem common to varying degrees in the new VBID studies is lack of specificity in the descriptions of sample construction. For example, only 1 included a sample selection flowchart to enable the reader to determine the effect of each sample inclusion and exclusion criterion, 69 although this information is considered a standard for research reporting. 72 Moreover, it was difficult to determine key details, such as the specific criteria used to define a "user" of a particular drug class or to qualify for DMP entry, in many reports. Similarly, in many VBID reports it was difficult or impossible to identify the preintervention values and/or the absolute change amounts for the outcome measures.
Still No Randomized Trials. As Roebuck et al. candidly acknowledge, even a well-done multivariate statistical analysis controlling for fixed effects (e.g., as a proxy for "healthy adherer" effects) is "not as good as a randomized controlled trial in establishing causality." 31 The report by Gibson et al. of the brand antidiabetic drug copayment reduction program is charge to employees. Unfortunately, the brand drugs were not named and the DMP was not described, making it difficult for decision makers to interpret or use the study results in estimating the costs and benefits of VBID. Finally, as in the other recent report by Gibson et al., the authors indicated that "the program was mostly cost-neutral to the company;" however, the measure of expenditures was "eligible charges," which was not defined specifically but appears to be a total (rather than a net after copayment) that does not represent the health plan sponsor's costs. 70 Unfortunately, in addition to failing to report the cost of the intervention to the health plan sponsor, none of the new VBID study reports contained even enough quantitative information for readers to calculate the intervention cost. Although most provided some information about mean copayment amounts paid per claim by the intervention and/or comparison groups before and/or after the intervention, only a few provided quantitative information for both time periods and groups, and none provided information about utilization (number of claims), which is essential to translating cost per claim into total cost. Additionally, tier-specific utilization data were not included in any of the new VBID study reports but are necessary to determine whether utilization shifts to drugs in higher or lower tiers affected payers' ingredient cost expenditures.

Problems in Study Design and/or Reporting.
Several problems in recent VBID research reports, including discrepancies between study methods and either methodological or clinical guidelines, are apparent (Appendix). For example, in an analysis of therapy discontinuation rates for a VBID program for antidiabetic medications, Chang et al. (2010) removed from the denominator patients who made a medication switch from one antidiabetic subclass to another (e.g., from a thiazolidinedione [TZD] to metformin or to a sulfonylurea). 29 This decision had the mathematical effect of inflating the discontinuation rate overall, and especially in the presence of even appropriate and desired switches from brand to therapeutically equivalent generic drugs, thereby systematically biasing the analysis to find higher "discontinuation" rates for the comparison group than the VBID group (Table 1). Unfortunately, the report does  Three key points about these calculations are noteworthy for payers. First, these figures illustrate the conclusion reached by Melnick and Motheral based on their VBID plausibility calculator that mathematically, it is nearly impossible for a health plan sponsor to achieve cost neutrality in VBID programs using medical cost offsets, with the possible exception of programs applied only to generic medications. 42 Assuming that a private payer incurs a cost of approximately $60,000 per patient for a major cardiovascular event (in 2006, costs per hospital stay billed to private insurance were $44,733 for coronary artery disease, $54,697 for MI, and $44,239 for stroke), 79 achieving cost neutrality for a VBID program that costs $29 PMPY in a plan with 100,000 members would require prevention of an additional 48 cardiovascular events per year ($2.9 million divided by $60,000). Thus, using clinical trial data as indicators of the baseline effectiveness of statins in preventing major cardiovascular events ( Table 2) [80][81][82] for the health plan's assumed 12,100 statin users (use prevalence of 12.1% × 100,000) and assuming a baseline MPR of 50%-80%, a VBID copayment reduction program that costs $29 PMPY would have to increase the effectiveness of statin treatment by approximately 41%-49% in secondary prevention (e.g., an increase of 48 over a baseline of 97 to 118 patients in whom events are prevented annually) and 68%-79% in primary prevention-despite increasing medication adherence by only about 4%-6% (3 percentage points improvement over a baseline MPR of 50%-80%) to break even. As VBID proponents have observed, additional cost offsets especially notable in this regard because its findings strongly suggest that the "effects" of the program were actually due to confounding. Specifically, the study found that among DMP participants, compliance with recommended screening and monitoring (i.e., primary care provider visits, hemoglobin A1c tests, lipid tests, and urinalysis) was higher for VBID enrollees than for comparison group patients. 71 However, the study report indicated that the VBID program changed pharmacy copayments only. There is no logically apparent causal linkage between pharmacy copayments and receipt of guideline-based medical care, and the study authors offered none in the report. Like the finding of Dormuth et al. (2009) that patients compliant with statin therapy were less likely than noncompliant patients to have automobile and workplace accidents, 76 the findings of Gibson et al. sound a cautionary note for those who attempt to equate association with causation; the resulting conclusions may be biologically or logically implausible.

Illustration of the Mathematical Effect of Removing Patients Making Medication Switches Before Calculating Discontinuation Rates
In contrast, an observational analysis by Maciejewski et al. (2010) is commendable for its inclusion of a comparison group of patients treated with therapy classes in which copayments were reduced in both the VBID intervention and comparison groups. The authors made the reasonable case that the lack of VBID "effect" in these classes, coupled with the positive association of VBID with adherence in the other study drug classes, strengthened the internal validity of their findings. 63 A study by Choudhry et al. of copayment elimination for statins and copayment reduction for clopidogrel, effective January 1, 2007, appears to have good internal validity; 68 however, the intervention was conducted among enrollees whose employer coupled widely publicized copayment reductions with intensive educational interventions in 2002, 77 making the context and external validity of the 2007 intervention unclear.

Costs and Benefits of VBID Interventions
The 2 new VBID studies with the strongest internal validity, one by Choudhry et al. and the other by Maciejewski et al., suggest a VBID effect size of approximately 1.5 to 4 percentage points in adherence measured by MPR or proportion of days covered (PDC). 63,68 Effect sizes of about 2.6 to 4.0 percentage points annually were reported previously by  for copayment reductions (for tier 1/tier 2/tier 3) from $5/$25/$45 to $0/$12.50/$22.50 for diabetes drugs, statins, and antihypertensive drugs (ACE inhibitors and angiotensin II receptor blockers [ARBs]). 78 Despite the statistical significance of MPR or PDC changes of 2 to 4 percentage points measured using large samples, these changes represent only 7 to 15 added days of therapy per year on average (e.g., 0.02 X 365 = 7.3 days).
The costs and benefits of these small adherence improvements have not yet been reported. In a previous editorial on the study by Chernew et al., we used national data to compensate for missing information in the study report and estimated that What Do We Really Know About VBID? Quality of the Evidence and Ethical Considerations for Health Plan Sponsors changes of 2.6 to 4.0 percentage points, Chernew et al. predicted that "because clinical evidence supports adherence to these medications, we expect health improvements, although we do not quantify them in this study." 78 In an accompanying press release from the sponsoring institution, the study's lead author speculated that "while future studies need to be done to actually quantify this specifically, there is considerable evidence that use of the classes of medication in this study will reduce the frequency of adverse clinical events and associated hospitalizations and ER visits." 15 However, about 2 years later, the research team reported that "preliminary statistical analysis of the spending data" for the VBID had "indicated considerable uncertainty surrounding estimates of the impact of the [VBID] intervention on aggregate spending," preventing econometric analyses of the data and prompting the investigators to develop a pharmacoeconomic model instead of analyzing the actual observed outcomes for the sample. 43 Unfortunately, no data on hospitalizations or ER visits-consequences of the "adverse clinical events" that the investigators had suggested would be prevented by the VBID-were reported.
Similarly, an analysis plan for a study of the MHealthy initiative, a VBID program that was implemented for University of Michigan employees and their dependents with diabetes on July 1, 2006, was published in April 2009. 83 The analysis plan indicated that study follow-up would end 30 months from improved worker productivity (e.g., reduced absenteeism and disability days), although not easily measured, are possible for active employee groups; 43 however, it is difficult to imagine that these effects would be substantial given the small size of the medication adherence effects.
Second, the results of the Maciejewski et al. analysis suggest, consistent with PBM observations, that the adherence effects of dispensing medication in 90-day supplies may overwhelm those of VBID. In the Maciejewski et al. analysis, enrollees with at least 1 pharmacy claim for a 90-day supply had adherence rates 17 to 22 percentage points higher than those of patients without any 90-day supplies. 63 Notably and unfortunately, none of the other new VBID studies reported utilization rates of 90-day supplies or mail order pharmacy or analyzed the effect of 90-day supplies on medication adherence.
Third, the need to calculate these "back-of-the-envelope" estimates from published research articles highlights deficiencies in the base of evidence about copayment reduction programs, especially for payers that need actionable, quantitative estimates of the impact of adherence promotion strategies on economic and clinical outcomes.

What to Expect When You're Expecting Information About VBID
In their 2008 report of the association of VBID with MPR What Do We Really Know About VBID? (an effect that is captured in the total cost measure), and (b) the reduction in copayment (an effect that is not captured in the total cost measure). Because of the inelasticity (lack of price responsiveness) in drug purchasing behavior in commercially insured groups, a calculation of total cost change in a VBID program will produce a small estimated effect that understates the actual cost of VBID to the payer. Yet, only 1 of the 3 reports, the economic "break-even" analysis by Chernew et al., 43 transparently disclosed in the study report the implications of the analytic perspective for plan sponsors. Thus, when provided with information about VBID costs and benefits, health plan sponsors should check carefully to determine if payer costs were measured.

Quality of the Evidence and Ethical Considerations for Health Plan Sponsors
Overextension. Completion of the first randomized trial of a copayment reduction intervention is expected in early 2011. 11 That study, the Post-MI FREEE (Free Rx and Economic Evaluation), is a test of eliminating copayments for secondary prevention medications (statins, beta-blockers, ACE inhibitors, and ARBs) for patients aged 64 years or younger following hospitalization for MI. 85 Because the baseline probability of adverse cardiovascular events is higher in a patient population with a previous MI than in the population of cardiovascular medication users as a whole, the likelihood of finding clinical benefits is higher in this patient sample than in a typical patient population in which medications are used both for primary and secondary prevention. Yet, an unfortunately common occurrence in health policy research is the overextension of findings from a study sample manifesting one set of characteristics to a larger population with completely different clinical or demographic characteristics. We have previously pointed out the frequent inappropriate extensions of a study conducted in a small group of low-income elderly with numerous chronic illnesses to healthier patient populations and to different outcomes-even to outcomes that were not studied in the original research. 86 In assessing the information presented in popular press accounts and literature reviews, payers should compare the assertions made about the Post-MI FREEE findings with the study report-or the study abstract for decision makers who lack the time to read the entire report-to determine if findings are represented accurately or misstated.

VBID: What Should Health Plan Sponsors Do Now?
We predicted in 2008 that managed care was approaching a crossroads at which policymakers would have to decide whether to reject cost-sharing policies based on high-quality evidence in favor of weaker, but more vigorously promoted, evidence. 58 That issue has become more acute and ethically important with the recent suggestions that the costs of drug copayment reductions-often for primary prevention using brand medications in therapeutic classes with generic alternatives-should be offset by increasing cost-sharing after implementation, or approximately January 2009, and that the analysis would assess the primary outcomes of medication utilization and adherence, as well as secondary outcomes including health care costs and utilization rates for outpatient visits, ER visits, and hospitalizations. 83 Although the MHealthy study follow-up was scheduled to end more than 2 years ago at this writing, to date the only reported findings of which we are aware include a brief mention, reported in a 2010 review article, of "preliminary results" indicating that the MHealthy intervention was associated with "a 7 percent increase in adherence to blood pressurelowering medication and a nonsignificant 4 percent increase in adherence to statins." 11 Against this shortfall of evidence promised but not yet reported, several reasons for a "caveat emptor" approach to VBID research are apparent, including the following key points.

Isolated Significant Findings.
Because of cumulative type 1 (false positive) error, it is mathematically expected that at least 1 finding in a series of numerous statistical tests will be statistically significant solely because of chance. For example, in 20 statistical tests at an alpha of 0.05, the probability of at least 1 false positive finding is 64%. 84 In the presence of publication bias, these multiple tests are not necessarily apparent to readers of a single research article. We encourage health plan sponsors to be mindful of the history of VBID research reporting (or nonreporting) in considering the results reported in any single publication, especially for hospitalizations and ER visits.
Causal Linkages. In viewing published results of observational studies of VBID programs, payers should consider whether the findings are plausible. For example, one would not expect large medical cost offsets from tiny medication adherence gains, large adherence gains from small cost-sharing changes, or changes in a measure of quality of care that is not affected by pharmacy copayments (e.g., receipt of guideline-based medical care, such as examinations and laboratory tests). Although understanding complex nuances of methodological and statistical techniques may be difficult for managed care decision makers who lack research training, consideration of basic clinical and practical causal logic is not difficult and will go a long way toward assessing the validity of VBID studies.

Total Cost Versus Health Plan Sponsor Cost: A Major
Difference for Payers. To date, 3 assessments of costs associated with VBID have either measured 70,71 or estimated 43 change in total cost, including both the payer cost and the patient cost share. Although this method is not inherently erroneous because it is common for health policy research to examine cost outcomes from a societal perspective, it produces a result that is uninformative for health plan sponsors making a decision about VBID. The financial effects of VBID on plan sponsors are the sum of (a) increased medication adherence What Do We Really Know About VBID? Quality of the Evidence and Ethical Considerations for Health Plan Sponsors requirements for patients using expensive treatments for serious or catastrophic illness. Assessment both of the evidence and, more importantly, the limitations of the evidence regarding VBID suggests 4 important steps going forward.
First, as Choudhry et al. observed in their recent review, important questions about the effects of drug copayment reductions on clinical and economic outcomes "should be answered before [VBID] is used more widely." 11 Because VBID has been associated with only minimal medication adherence increases documented only in observational research, and because no health or medical utilization outcomes (e.g., ER or hospital use) have yet been reported for VBID programs, the evidence is insufficient to support expanding its use at the present time.
Second, managed care decision makers should refuse to accept studies that lack transparent reporting necessary to make even basic estimates of the costs and benefits of VBID. Nontransparent study reports do not provide useful information and should not be used for policymaking. For promulgators of research information, the logical corollary is that continuing to publish suboptimal work will eventually cause decision makers to be indifferent to study findings-exactly the opposite of the goal that the AHRQ has set for evidencebased decision making in health care policy.
Third and related, although it would seem that health care decision makers should not have to be responsible for critical appraisal of the information provided in peer-reviewed articles, it appears that such critique is unfortunately necessary in costsharing research because of a pattern of inaccurate statements about research findings. In reading literature reports about VBID, health care decision makers will find it helpful to read the source materials-at least the study abstract and the results tables if time is short-instead of relying solely on secondary descriptions of what previous research has shown. Summary study tables including critical appraisal of the evidence, such as those that we have reported here and in previous JMCP issues, 58 as well as that reported by Motheral in the current issue 87 are also helpful, and we encourage other health policy researchers to provide summaries of this type for health care decision makers.
Fourth, and most important from a policy perspective, deliberations about whether to fund drug copayment reductions, especially for primary prevention, by directing scarce resources away from a subset of prescribed medical and pharmaceutical treatments should demand high-quality evidence. Yet at this writing, nearly a decade after pharmacy benefit copayment reduction was initially proposed as a means to improve the outcomes of patients with chronic health conditions, health plan sponsors have little of the information that they need to assess the costs and benefits of VBID. Available evidence is of suboptimal quality, much of it so opaque that it is uninterpretable; outcomes critically important to enrollees and

Authors
health plan sponsors, such as cost to the payer and effects on generic drug utilization and patient health, remain either unexamined or unreported; and the only randomized trial of VBID of which we are aware, the Post-MI FREEE, is laudable for its design and transparency but limited to secondary prevention. An evidence base that falls so far short of the AHRQ's ideal for health care policy research-timely, clear, transparent, solid, and actionable-should be viewed as an example of how not to inform health care system change.

DISCLOSURES
The authors report no financial conflicts of interest related to the subjects or products discussed in this article. Fairman reports that she works and volunteers a few hours each month in nursing homes, primarily with bedbound patients who have catastrophic illnesses.

Summary of Recent Observational Studies of Copayment Reductions and Medication Adherence a
Chang (2010) 29 Overview: Study of copayment reductions for antidiabetic medications-free generics and insulin, reductions in copayments for tier 2 brand drugs, no change for tier 3, effective January 1, 2007; study period was January 1, 2006, through December 31, 2007.

Sample
Enrollees with at least 1 claim for an antidiabetic medication during the study period, classified as initiators (no claims in 2006) and continuers/discontinuers (use in 2006 including final 45 days of the year); all were continuously enrolled throughout the study period.

Groups
Intervention: 3 PBM clients without concurrent educational or DSM programs; n = 20,173 (however, outcomes were reported for only 2,538 patients). Copayments changed from $15 to $0 for generic; $30 to a range of $10-$15 for tier 2; a range of $30-$35 for tier 3 in both periods; mean copayments changed from $28 to $0 for insulin and from $21 to $10 for OADs. Comparison: PBM clients without VBID; n = 190,889 (however, outcomes were reported for only 8,912 patients), matched on "adjudication platform," client type, benefit characteristics including "mail or retail coverage," and "mean out-of-pocket costs at the group level;" and by demographic characteristics and geographic region at the individual level. Copayments were $10 for tiers 1 and 2 in both periods, b and ranged from $30-$35 for tier 3 in both periods; insulin mean changed from $23 to $28 and OAD mean was $18 in both periods.

Analysis
Comparisons of MPR, treatment initiation and DC rates pre-intervention vs. post-intervention for intervention and comparison groups; DC rate calculations excluded patients switching to a different therapeutic antidiabetic subclass. Logistic regression models of discontinuation and linear regression models of MPR adjusted for age, sex, and mail order use.

Results
• Treatment initiation rates were 2.3% intervention vs.

Comments
• Calculations difficult to interpret because of missing information in study data tables, especially presentation of data for only a small fraction of study cases. • Pre-intervention values of most outcome variables not reported, making it difficult to interpret the practical/clinical significance of study results. • Prior to the intervention, use prevalence rates were about 1-2 percentage points higher, and the percentage with MPR more than 80% was much lower, in the VBID group than the comparison group; MPR change results could represent RTM, but pre-intervention MPRs were not documented, making RTM effects difficult to ascertain. • The effect of $4 generic programs among large community pharmacies is unknown; it is possible that higher treatment "initiation" rates reflect switch from $4 generics (not in database and paid by patient) to $0 generics (in database and paid by health plan sponsor). • The decision to exclude from the DC calculation patients who made a subclass switch (a) masked the potentially positive result of switching to lower cost medication and (b) artificially inflated DC rates in presence of elevated switch rates (Table 1), thereby biasing the analysis to find higher DC rates in the comparison group. • Insulin copayments increased by 22% in the comparison group from pre-to post-intervention. Choudhry (2010) 68 Overview: Study of elimination of all statin copayments for patients with vascular disease or diabetes and reduction of copayments for clopidogrel, effective January 1, 2007.

Sample
Patients who from January 2006 through December 2007 either (a) had at least 1 statin claim and proxy measure for diabetes and vascular disease (at least 1 claim for diabetes medication or supply, beta blocker, or platelet inhibitor) or (b) had at least 1 claim for clopidogrel; there was no continuous enrollment requirement for sample inclusion.

Groups
Intervention: Employees and dependents of Pitney Bowes; n = 2,051 statins and 779 clopidogrel; mean copayments changed from $24.18 to $0.60 for statins and from $17.22 to $8.86 for clopidogrel. Comparison: Commercially insured enrollees of BCBS-NJ who used the same PBM; n = 38,174 statins and 11,627 clopidogrel; mean copayments changed from $11.80 to $11.95 for statins and from $10.65 to $14.43 for clopidogrel.

Analysis
Interrupted time series of monthly PDC from January 2006 through December 2007; GEE models controlled for demographics, ZIP level data, and comorbidities.

Results
• Unadjusted: Statin PDC 2.8 percentage points higher for VBID than comparison "immediately after" implementation; clopidogrel PDC 4.0 percentage points higher for VBID than comparison 12 months post-implementation. • Adjusted: 3.1 percentage point "immediate" increase in PDC level for statins; 4.2 percentage point "immediate" increase in PDC level for clopidogrel; no significant changes in slope in either group.

Comments
• Pitney Bowes implemented widely publicized copayment reductions and education beginning in 2002, 5 years prior to this copayment reduction; c context of present study not clear. Analysis "unable to account" for the extent of participation in DMPs that were available to both study groups. • Mean copayment in comparison group was essentially unchanged for statins in pre-and post-intervention periods but increased by 35% (from $10.65 to $14.43) for clopidogrel. • Generic simvastatin became available in June 2006, midway through the pre-intervention period; it is not clear whether plans encouraged switches to generic simvastatin during post-implementation period. • Positive methodological decisions included the following: (a) days spent in a hospital or nursing home were subtracted from the denominator; (b) statin PDC accounted for all drugs (i.e., switching did not count against PDC); and (c) numerous sensitivity analyses were performed (producing similar findings).